House-Prices Advanced Regression Techniques Competition Solution

Prediction of hospital stay duration in heart failure patients using machine learning.

This repo contains the project jupyter notebooks and data files to view and re-run my analysis of the flight data.

tidyverse, doParallel, caret, randomForest, pdp, glmnet

This project develops a machine learning model to predict the salaries of baseball players based on their past performance.

Example machine learning applications for the determination of the residual yield force of corroded steel bars tested under monotonic tensile loading. Data is collected from 26 experimental programs avaialbe in the literature.

ML Project implementing ANN, SVM, Random Forest, Elastic Net regression models from scratch.

A forecasting system for multiple sectors that uses ARIMA, ETS, SVR, and other models displayed on a user friendly interface with different viewing options.

svm approach to predict the tolerance rates in bacterial infections. It uses eps-regression.

Repository used for the subject Artificial Intelligence.

Predict wine quality based on chemical composition

Support Vector Regression (SVR) implementation to assess power consumption, utilizing three models: linear, poly, and rbf. The final outcomes are presented in terms of Mean Squared Error (MSE) and R-squared (R2).

Machine Learning Model to predict payment date for the invoices using XGBoost Regressor.

In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).

This is about analyzing the impact of climate change on the yield of the 4 food crops for 41 years. It aims to uncover the intricate relationship between climatic factors & the yield of crops, identify, quantify the kind of relationship. Also, apply machine learning(ML) Algorithms, Optimize, develop predictive models and compare the perf metrics

Releases Github Analyzer

This repository contains a machine learning project focused on predicting the survival of passengers on the Titanic. The project uses a Support Vector Regression (SVR) model from the sklearn library and involves data preprocessing and prediction.

California Housing Price Prediction - Linear Regression, Support Vector Regression, Decision Trees, and Random Forest Regression

The project aims to predict house prices in California based on various features using machine learning techniques. It uses the California housing dataset, comprising 20640 data entries and 8 attributes, with the target being the house price.

A web based tool to predict lung health severity in COVID-19 patients